source("002-LoadData.R")

library(stats)
library(forcats)
library(effsize)
library(clinfun)
library(ggplot2)
library(reshape2)



digiArea <- c("element_density","tag_density","user_density","area_diversity")
contribIndepVar <- c("quantity","discussion_size","notes_size")

## statistics on seniors
for (variableName in names(dependentV.changes)){
  print("")
  print("========================================================================")
  print(paste("RESULTS FOR VARIABLE",variableName))
  print("========================================================================")
  print("")
  print("")
  
  jitterplot <- ggplot(dependentV.changes,aes(x=independentV.mappers$timeRange,
                                              y=dependentV.changes[,variableName]))+
    geom_count(position="jitter",aes(color=independentV.mappers$HappeningType))+
    labs(title=variableName)+
    scale_color_manual(values=c("#8c510a","#01665e","#5ab4ac"))+
    theme(legend.title = element_blank(),
          axis.title.x = element_blank(),
          axis.title.y=element_blank())+
    scale_y_continuous(trans='pseudo_log')
  print(jitterplot)
  
  print("")
  
  lineplot <- ggplot(dependentV.changes,aes(x=independentV.mappers$timeRange,
                                            group=interaction(independentV.mappers$Mapperid,independentV.mappers$Happeningid),
                                            y=dependentV.changes[,variableName]))+
    labs(title=variableName)+
    scale_color_manual(values=c("#8c510a","#01665e","#5ab4ac"))+
    theme(legend.title = element_blank(),
          axis.title.x = element_blank(),
          axis.title.y=element_blank())+
    geom_line(aes(color=independentV.mappers$HappeningType))+
    scale_y_continuous(trans='pseudo_log')
  print(lineplot)
  
  print("")
  print("Boxplot on contributors only: ")
  
  boxplot <- ggplot(dependentV.changes[independentV.mappers$contribBefore>0&
                                         independentV.mappers$contribAfter>0,],
                    aes(x=independentV.mappers[independentV.mappers$contribBefore>0&
                                                 independentV.mappers$contribAfter>0,"timeRange"],
                        color=independentV.mappers[independentV.mappers$contribBefore>0&
                                                     independentV.mappers$contribAfter>0,"HappeningType"],
                        y=dependentV.changes[independentV.mappers$contribBefore>0&
                                               independentV.mappers$contribAfter>0,variableName]))+
    geom_boxplot()+
    labs(title=variableName)+
    scale_color_manual(values=c("#8c510a","#01665e","#5ab4ac"))+
    theme(legend.title = element_blank(),
          axis.title.x = element_blank(),
          axis.title.y=element_blank())+
    scale_y_continuous(trans='pseudo_log')
  print(boxplot)
  
  print("")
  
  for(i in levels(independentV.mappers$timeRange)){
    
    #skip forbidden variables
    if(i=="one month"&any(digiArea==variableName)){
      next
    }
    
    #get data for time interaval and variable
    if(any(contribIndepVar==variableName)){
      variable <- dependentV.changes[independentV.mappers$timeRange==i,variableName]
      classes <- independentV.mappers[independentV.mappers$timeRange==i,"HappeningType"]
    }else{
      variable <- dependentV.changes[independentV.mappers$timeRange==i&
                                       independentV.mappers$contribBefore>0&
                                       independentV.mappers$contribAfter>0,variableName]
      classes <- independentV.mappers[independentV.mappers$timeRange==i&
                                        independentV.mappers$contribBefore>0&
                                        independentV.mappers$contribAfter>0,"HappeningType"]
    }

    
    print("")
    print(paste("Time frame: ",i))
    print("")
    print("N:")
    print(summary(classes))
    print("")
    print(paste("Summary Statistics for variable ",variableName))
    print(aggregate(variable,by=list(classes),FUN=summary))
    print("")
    
    #kruskal test
    kruskal <- kruskal.test(x=variable,g=classes)
    if(kruskal$p.value<=0.05){

      print("")
      print(paste(variableName,"is significantly influenced by an event for",i))
      print("")
      print("")
      
      # wilcox pariwise post hoc
      #http://www.sthda.com/english/wiki/kruskal-wallis-test-in-r
      wilcox <- pairwise.wilcox.test(x=variable,g=classes,p.adjust.method = "BH")
      print("Pairwise comparison: ")
      print(wilcox$p.value)

      
      # mode IVs for CFM
      if(wilcox$p.value["CFM","CG"]<=0.05){
        print(paste("Cohends d for effect size of the CFM on",variableName,":"))
        print(cohen.d(d=variable[classes!="CRM"],f=fct_drop(classes[classes!="CRM"])))
        print("")
        
        if(any(contribIndepVar==variableName)){
          variable1 <- dependentV.changes[independentV.mappers$timeRange==i&
                                          independentV.mappers$HappeningType=="CFM",variableName]
          #skill
            classes1 <- independentV.mappers[independentV.mappers$timeRange==i&
                                       independentV.mappers$HappeningType=="CFM","skill"]
        }else{
          variable1 <- dependentV.changes[independentV.mappers$timeRange==i&
                                            independentV.mappers$contribBefore>0&
                                            independentV.mappers$contribAfter>0&
                                            independentV.mappers$HappeningType=="CFM",variableName]
          #skill
          classes1 <- independentV.mappers[independentV.mappers$timeRange==i&
                                             independentV.mappers$contribBefore>0&
                                             independentV.mappers$contribAfter>0&
                                             independentV.mappers$HappeningType=="CFM","skill"]
        }
        print("N:")
        print(length(classes1))
        model <- lm(variable1~classes1)
        if(any(summary(model)$coefficients[2,4]<=0.05)){
          print("Analyses of the effect of skill for CFM")
          { sink("/dev/null"); print(plot(classes1,variable1,log="x",main="The skill has an effect",
                                          sub=paste("on this variable (",variableName,") for CFM"))); sink(); }
          print(abline(model))
          print(plot.new())
          print(summary(model))
          print("")
        }
        if(any(contribIndepVar==variableName)){
        # economic status
        classes1 <- independentV.mappers[independentV.mappers$timeRange==i&
                                           independentV.mappers$HappeningType=="CFM","economic_status"]
        }else{
          # economic status
          classes1 <- independentV.mappers[independentV.mappers$timeRange==i&
                                             independentV.mappers$contribBefore>0&
                                             independentV.mappers$contribAfter>0&
                                             independentV.mappers$HappeningType=="CFM","economic_status"]
        }
        
        jockey <- jonckheere.test(variable1,classes1,nperm=1000)
          print("N:")
          print(summary(classes1))
          print("")
          print("Summary Statistics: ")
          print(aggregate(variable1,by=list(classes1),FUN=summary))
          print("")
        if(jockey$p.value<=0.05){
          wilcox2 <- pairwise.wilcox.test(x=variable1,g=classes1,p.adjust.method = "BH")
          if(any(wilcox2$p.value<=0.05,na.rm=TRUE)){
            print("Pairwise comparison: ")
            print(wilcox2$p.value)
            print(paste("Analyses of the effect of the economic status for CFM with a p-value of",jockey$p.value))
            { sink("/dev/null"); print(plot(x=classes1,
                                            y=variable1,
                                            main="The economic status has an effect",
                                            sub=paste("on this variable (",variableName,") for CFM"))); 
              sink(); }
            print(plot.new())
            print("")
          }
        }
        
        #culture
          if(any(contribIndepVar==variableName)){
        classes1 <- independentV.mappers[independentV.mappers$timeRange==i&
                                           independentV.mappers$HappeningType=="CFM","culture"]
          }else{
            classes1 <- independentV.mappers[independentV.mappers$timeRange==i&
                                               independentV.mappers$contribBefore>0&
                                               independentV.mappers$contribAfter>0&
                                               independentV.mappers$HappeningType=="CFM","culture"]
          }
        classes1 <- fct_drop(fct_lump_min(classes1,min=10))

        print("N:")
        print(summary(classes1))
        print("")
        print("Summary Statistics: ")
        print(aggregate(variable1,by=list(classes1),FUN=summary))
        print("")
        
        if(length(levels(classes1))>1){
          kruskal2 <- kruskal.test(x=variable1,g=classes1)
          if(kruskal2$p.value<=0.05){
            wilcox2 <- pairwise.wilcox.test(x=variable1,g=classes1,p.adjust.method = "BH")
            if(any(wilcox2$p.value<=0.05,na.rm=TRUE)){
              print("")
              print(paste(variableName,"is significantly influenced by at least one culture for CFM with p=",kruskal2$p.value))
              print("")
              print("Pairwise comparison: ")
              print(wilcox2$p.value)
              { sink("/dev/null"); print(plot(classes1,variable1,main="The culture has an effect",
                                              sub=paste("on this variable (",variableName,") for CFM"))); sink(); }
              print(plot.new())
              print("")
            }
          }
        }
        
        
        
        
      }
      
      # other IVs for CRM
      if(wilcox$p.value["CRM","CG"]<=0.05){
        print(paste("Cohends d for effect size of the CRM on",variableName,":"))
        print(cohen.d(d=variable[classes!="CFM"],f=fct_drop(classes[classes!="CFM"])))
        print("")
        
        if(any(contribIndepVar==variableName)){
            #skill
          variable2 <- dependentV.changes[independentV.mappers$timeRange==i&
                                          independentV.mappers$HappeningType=="CRM",variableName]
          classes2 <- independentV.mappers[independentV.mappers$timeRange==i&
                                           independentV.mappers$HappeningType=="CRM","skill"]
        }else{
          #skill
          variable2 <- dependentV.changes[independentV.mappers$timeRange==i&
                                            independentV.mappers$contribBefore>0&
                                            independentV.mappers$contribAfter>0&
                                            independentV.mappers$HappeningType=="CRM",variableName]
          classes2 <- independentV.mappers[independentV.mappers$timeRange==i&
                                             independentV.mappers$contribBefore>0&
                                             independentV.mappers$contribAfter>0&
                                             independentV.mappers$HappeningType=="CRM","skill"]
        }
        print("N:")
        print(length(classes2))
        print("")
        model <- lm(variable2~classes2)
        if(any(summary(model)$coefficients[2,4]<=0.05,na.rm = TRUE)){
          print("Analyses of the effect of skill for CRM")
          { sink("/dev/null"); print(plot(classes2,variable2,log="x",main="The skill has an effect",
                                          sub=paste("on this variable (",variableName,") for CRM"))); sink(); }
          print(abline(model))
          print(plot.new())
          print(summary(model))
          print("")
        }

        if(any(contribIndepVar==variableName)){
          ## distance during event
          classes2 <- independentV.mappers[independentV.mappers$timeRange==i&
                                           independentV.mappers$HappeningType=="CRM","event_mapping_distance"]
        }else{
          ## distance during event
          classes2 <- independentV.mappers[independentV.mappers$timeRange==i&
                                             independentV.mappers$contribBefore>0&
                                             independentV.mappers$contribAfter>0&
                                             independentV.mappers$HappeningType=="CRM","event_mapping_distance"]
        }
        print("N:")
        print(length(classes2))
        print("")
        model <- lm(variable2~classes2)
        if(any(summary(model)$coefficients[2,4]<=0.05)){
          print("Analyses of the effect of the distance to the Region mapped during the event for CRM")
          { sink("/dev/null"); print(plot(classes2,variable2,log="x",main="The event mapping distance has an effect",
                                          sub=paste("on this variable (",variableName,") for CRM"))); sink(); }
          print(abline(model))
          print(plot.new())
          print(summary(model))
          print("")
        }
      }
      
      # between happenings
      if(wilcox$p.value["CRM","CFM"]<=0.05){
        print(paste("Cohends d for effect size between CRM and CFM on",variableName,":"))
        print(cohen.d(d=variable[classes!="CG"],f=fct_drop(classes[classes!="CG"])))
        print("")
      }
    }
    print("")
    print("")
    print("--------------------------------------------------------------------------------")
    print("")
    print("")
  }
}
## [1] ""
## [1] "========================================================================"
## [1] "RESULTS FOR VARIABLE quantity"
## [1] "========================================================================"
## [1] ""
## [1] ""

## [1] ""

## [1] ""
## [1] "Boxplot on contributors only: "
## [1] ""
## [1] ""
## [1] "Time frame:  one month"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
## 218 123 189 
## [1] ""
## [1] "Summary Statistics for variable  quantity"
##   Group.1      x.Min.   x.1st Qu.    x.Median      x.Mean   x.3rd Qu.
## 1      CG  -1.0000000   0.0000000   0.0000000   0.2461348   0.0000000
## 2     CFM  -1.0000000  -0.1330458   1.0000000   2.9434328   2.6000834
## 3     CRM  -1.0000000   0.0000000   0.0000000   4.7565906   1.0000000
##        x.Max.
## 1  25.7272727
## 2  81.4210526
## 3 282.1875000
## [1] ""
## [1] ""
## [1] "quantity is significantly influenced by an event for one month"
## [1] ""
## [1] ""
## [1] "Pairwise comparison: "
##               CG        CFM
## CFM 1.687748e-08         NA
## CRM 1.896750e-03 0.00189675
## [1] "Cohends d for effect size of the CFM on quantity :"
## 
## Cohen's d
## 
## d estimate: -0.4908005 (small)
## 95 percent confidence interval:
##      lower      upper 
## -0.7156782 -0.2659227 
## [1] ""
## [1] "N:"
## [1] 123
## [1] "N:"
##          low income lower middle income upper middle income 
##                   5                   9                  33 
##         high income 
##                  76 
## [1] ""
## [1] "Summary Statistics: "
##               Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean
## 1          low income -0.883272449  0.353499407  4.946595461  3.792411572
## 2 lower middle income -0.534629405  0.096224156  1.000000000  0.904327761
## 3 upper middle income -1.000000000 -0.615384615  0.000000000  1.335589161
## 4         high income -1.000000000 -0.006322957  1.000000000  3.827194473
##      x.3rd Qu.       x.Max.
## 1  6.820567376  7.724668064
## 2  1.000000000  3.243902439
## 3  1.000000000 20.886363636
## 4  3.193096377 81.421052632
## [1] ""
## [1] "N:"
##        Japanese Latin  American        Orthodox         Western 
##              18              35              11              54 
##           Other 
##               5 
## [1] ""
## [1] "Summary Statistics: "
##           Group.1     x.Min.  x.1st Qu.   x.Median     x.Mean  x.3rd Qu.
## 1        Japanese -0.3333333  0.5544925  1.8795219  8.0677528  5.6646825
## 2 Latin  American -1.0000000 -0.6360505  0.0000000  1.1421828  1.0000000
## 3        Orthodox -1.0000000  0.0000000  0.7656250  0.5953268  1.0000000
## 4         Western -1.0000000 -0.1656289  1.0000000  2.7477578  2.7843211
## 5           Other  0.3534994  2.0734317  4.9465955  4.3837524  6.8205674
##       x.Max.
## 1 81.4210526
## 2 20.8863636
## 3  2.8356808
## 4 27.5000000
## 5  7.7246681
## [1] ""
## Warning in wilcox.test.default(xi, xj, paired = paired, ...): cannot
## compute exact p-value with ties

## Warning in wilcox.test.default(xi, xj, paired = paired, ...): cannot
## compute exact p-value with ties

## Warning in wilcox.test.default(xi, xj, paired = paired, ...): cannot
## compute exact p-value with ties

## Warning in wilcox.test.default(xi, xj, paired = paired, ...): cannot
## compute exact p-value with ties

## Warning in wilcox.test.default(xi, xj, paired = paired, ...): cannot
## compute exact p-value with ties

## [1] ""
## [1] "quantity is significantly influenced by at least one culture for CFM with p= 0.00199138224393104"
## [1] ""
## [1] "Pairwise comparison: "
##                    Japanese Latin  American   Orthodox   Western
## Latin  American 0.005395134              NA         NA        NA
## Orthodox        0.041315287      0.49646492         NA        NA
## Western         0.067004881      0.10472179 0.53820322        NA
## Other           0.538203216      0.04131529 0.05663624 0.1180635

## NULL
## [1] ""
## [1] "Cohends d for effect size of the CRM on quantity :"
## 
## Cohen's d
## 
## d estimate: -0.2591213 (small)
## 95 percent confidence interval:
##       lower       upper 
## -0.45531797 -0.06292461 
## [1] ""
## [1] "N:"
## [1] 189
## [1] ""
## [1] "N:"
## [1] 189
## [1] ""
## [1] "Cohends d for effect size between CRM and CFM on quantity :"
## 
## Cohen's d
## 
## d estimate: -0.08838066 (negligible)
## 95 percent confidence interval:
##      lower      upper 
## -0.3164376  0.1396762 
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  six months"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
## 185 102 139 
## [1] ""
## [1] "Summary Statistics for variable  quantity"
##   Group.1      x.Min.   x.1st Qu.    x.Median      x.Mean   x.3rd Qu.
## 1      CG  -1.0000000  -0.8340860   0.0000000   1.4068888   1.0000000
## 2     CFM  -1.0000000  -0.5862802   0.0000000   1.6199766   1.0000000
## 3     CRM  -1.0000000  -0.8623970   0.0000000   5.9681038   0.9982794
##        x.Max.
## 1 149.0000000
## 2  62.4064855
## 3 493.6666667
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  one year"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
## 168  93 115 
## [1] ""
## [1] "Summary Statistics for variable  quantity"
##   Group.1        x.Min.     x.1st Qu.      x.Median        x.Mean
## 1      CG   -1.00000000   -0.95984250    0.00000000    1.48590036
## 2     CFM   -1.00000000   -0.45007873    0.00000000   18.31582607
## 3     CRM   -1.00000000   -0.28478303    0.01215399    4.50115580
##       x.3rd Qu.        x.Max.
## 1    0.20480549  159.57142857
## 2    1.00000000 1413.50000000
## 3    1.00000000  210.05128205
## [1] ""
## [1] ""
## [1] "quantity is significantly influenced by an event for one year"
## [1] ""
## [1] ""
## [1] "Pairwise comparison: "
##               CG       CFM
## CFM 0.0054324572        NA
## CRM 0.0004748266 0.6397987
## [1] "Cohends d for effect size of the CFM on quantity :"
## 
## Cohen's d
## 
## d estimate: -0.191 (negligible)
## 95 percent confidence interval:
##       lower       upper 
## -0.44604277  0.06404267 
## [1] ""
## [1] "N:"
## [1] 93
## [1] "N:"
##          low income lower middle income upper middle income 
##                   2                   9                  22 
##         high income 
##                  60 
## [1] ""
## [1] "Summary Statistics: "
##               Group.1        x.Min.     x.1st Qu.      x.Median
## 1          low income   23.47872340   36.02262280   48.56652220
## 2 lower middle income   -0.38924615    0.00000000    1.00000000
## 3 upper middle income   -1.00000000   -0.91499504   -0.33764365
## 4         high income   -1.00000000   -0.36276470    0.04642127
##          x.Mean     x.3rd Qu.        x.Max.
## 1   48.56652220   61.11042159   73.65432099
## 2    1.10675154    1.00000000    4.31669188
## 3   -0.11790864    0.00000000    5.37133183
## 4   26.64786678    1.08003673 1413.50000000
## [1] ""
## [1] "N:"
##        Japanese Latin  American         Western           Other 
##              16              25              43               9 
## [1] ""
## [1] "Summary Statistics: "
##           Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean
## 1        Japanese   -0.9448231   -0.3266622    0.6634430    4.7265037
## 2 Latin  American   -1.0000000   -0.3659926    0.0000000    3.1947887
## 3         Western   -1.0000000   -0.4196624    0.1492206   35.5212450
## 4           Other   -0.9332344   -0.9022604   -0.3775147    2.2738347
##      x.3rd Qu.       x.Max.
## 1    1.5734435   63.5558376
## 2    0.1432343   73.6543210
## 3    1.4611650 1413.5000000
## 4    0.0000000   23.4787234
## [1] ""
## [1] "Cohends d for effect size of the CRM on quantity :"
## 
## Cohen's d
## 
## d estimate: -0.1717424 (negligible)
## 95 percent confidence interval:
##       lower       upper 
## -0.41040448  0.06691971 
## [1] ""
## [1] "N:"
## [1] 115
## [1] ""
## [1] "N:"
## [1] 115
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  two years"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
## 133  76  85 
## [1] ""
## [1] "Summary Statistics for variable  quantity"
##   Group.1        x.Min.     x.1st Qu.      x.Median        x.Mean
## 1      CG    -1.0000000    -0.9098901     0.0000000     1.2974271
## 2     CFM    -1.0000000    -0.6596083    -0.1750173   203.5083222
## 3     CRM    -1.0000000    -0.1915633     0.0000000   265.0007132
##       x.3rd Qu.        x.Max.
## 1     1.0000000    51.0000000
## 2     1.0000000 14923.0000000
## 3     1.0000000 22191.0000000
## [1] ""
## [1] ""
## [1] "quantity is significantly influenced by an event for two years"
## [1] ""
## [1] ""
## [1] "Pairwise comparison: "
##             CG       CFM
## CFM 0.22943493        NA
## CRM 0.03939687 0.2294349
## [1] "Cohends d for effect size of the CRM on quantity :"
## 
## Cohen's d
## 
## d estimate: -0.1757132 (negligible)
## 95 percent confidence interval:
##       lower       upper 
## -0.44991935  0.09849296 
## [1] ""
## [1] "N:"
## [1] 85
## [1] ""
## [1] "N:"
## [1] 85
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "========================================================================"
## [1] "RESULTS FOR VARIABLE creations_share"
## [1] "========================================================================"
## [1] ""
## [1] ""

## [1] ""

## [1] ""
## [1] "Boxplot on contributors only: "

## [1] ""
## [1] ""
## [1] "Time frame:  one month"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  32  84  61 
## [1] ""
## [1] "Summary Statistics for variable  creations_share"
##   Group.1        x.Min.     x.1st Qu.      x.Median        x.Mean
## 1      CG -0.6575342466 -0.1001557838  0.0000000000 -0.0236385337
## 2     CFM -1.0000000000 -0.1260608171  0.0008886685 -0.0065046870
## 3     CRM -1.0000000000 -0.1731707317  0.0153846154 -0.0009941808
##       x.3rd Qu.        x.Max.
## 1  0.0800928859  0.7352941176
## 2  0.1298748228  0.6479357173
## 3  0.1785189847  0.9265822785
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  six months"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  65  81  71 
## [1] ""
## [1] "Summary Statistics for variable  creations_share"
##   Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean    x.3rd Qu.
## 1      CG -0.687500000 -0.225043155 -0.043773196 -0.022170388  0.108294931
## 2     CFM -0.880052269 -0.149991446 -0.007546221 -0.032963735  0.118490292
## 3     CRM -0.682670988 -0.223181306 -0.009322034 -0.033375710  0.134105284
##         x.Max.
## 1  1.000000000
## 2  0.698911025
## 3  0.603887147
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  one year"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  59  68  58 
## [1] ""
## [1] "Summary Statistics for variable  creations_share"
##   Group.1        x.Min.     x.1st Qu.      x.Median        x.Mean
## 1      CG -0.5598287795 -0.1113595252  0.0246382121  0.0556706741
## 2     CFM -0.6937962834 -0.1811453206  0.0024083534 -0.0005635426
## 3     CRM -0.8254548138 -0.1906173477 -0.0490154145 -0.0332562716
##       x.3rd Qu.        x.Max.
## 1  0.1880443988  1.0000000000
## 2  0.1060103926  0.7235772358
## 3  0.1220621981  0.8350140056
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  two years"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  63  63  49 
## [1] ""
## [1] "Summary Statistics for variable  creations_share"
##   Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean    x.3rd Qu.
## 1      CG -0.980769231 -0.243653988 -0.040670981 -0.044102018  0.180815219
## 2     CFM -0.757852968 -0.233930875 -0.003676308 -0.030150397  0.091889002
## 3     CRM -0.444640962 -0.232972226 -0.058525660  0.001258369  0.186596562
##         x.Max.
## 1  0.762711864
## 2  0.692084942
## 3  0.750000000
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "========================================================================"
## [1] "RESULTS FOR VARIABLE tag_changes_share"
## [1] "========================================================================"
## [1] ""
## [1] ""

## [1] ""

## [1] ""
## [1] "Boxplot on contributors only: "

## [1] ""
## [1] ""
## [1] "Time frame:  one month"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  32  84  61 
## [1] ""
## [1] "Summary Statistics for variable  tag_changes_share"
##   Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean    x.3rd Qu.
## 1      CG -1.000000000 -0.125896934 -0.001194743 -0.047675820  0.048508793
## 2     CFM -0.824561404 -0.093929255  0.001476258  0.031458367  0.117949847
## 3     CRM -0.350911434 -0.043543689  0.000000000  0.051776615  0.079487179
##         x.Max.
## 1  0.500000000
## 2  1.000000000
## 3  0.755555556
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  six months"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  65  81  71 
## [1] ""
## [1] "Summary Statistics for variable  tag_changes_share"
##   Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean    x.3rd Qu.
## 1      CG -1.000000000 -0.083703131  0.007955372 -0.004191702  0.113333333
## 2     CFM -1.000000000 -0.039142494  0.033778273  0.053798004  0.111204268
## 3     CRM -0.299529914 -0.027392648  0.005788712  0.038542300  0.050409547
##         x.Max.
## 1  0.812500000
## 2  0.906474820
## 3  0.538815067
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  one year"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  59  68  58 
## [1] ""
## [1] "Summary Statistics for variable  tag_changes_share"
##   Group.1        x.Min.     x.1st Qu.      x.Median        x.Mean
## 1      CG -1.0000000000 -0.0959909656 -0.0151564829 -0.0174636738
## 2     CFM -0.6914285714 -0.0597715343 -0.0008795558 -0.0191133312
## 3     CRM -0.3805507508 -0.0684707344 -0.0029411765  0.0100766112
##       x.3rd Qu.        x.Max.
## 1  0.1285256410  0.5855555556
## 2  0.0426491713  0.6781811865
## 3  0.0495519066  0.8835978836
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  two years"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  63  63  49 
## [1] ""
## [1] "Summary Statistics for variable  tag_changes_share"
##   Group.1      x.Min.   x.1st Qu.    x.Median      x.Mean   x.3rd Qu.
## 1      CG -0.92592593 -0.10919081  0.02076883  0.08064153  0.26791366
## 2     CFM -0.69599211 -0.11429731 -0.01200083  0.02146650  0.15358865
## 3     CRM -0.37326131 -0.07076923 -0.01140615 -0.02476001  0.02526892
##        x.Max.
## 1  0.89900111
## 2  0.77056277
## 3  0.33557800
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "========================================================================"
## [1] "RESULTS FOR VARIABLE geometry_changes_share"
## [1] "========================================================================"
## [1] ""
## [1] ""

## [1] ""

## [1] ""
## [1] "Boxplot on contributors only: "

## [1] ""
## [1] ""
## [1] "Time frame:  one month"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  32  84  61 
## [1] ""
## [1] "Summary Statistics for variable  geometry_changes_share"
##   Group.1      x.Min.   x.1st Qu.    x.Median      x.Mean   x.3rd Qu.
## 1      CG -0.52941176 -0.12862564  0.01543608  0.05476847  0.14676408
## 2     CFM -0.50246508 -0.10427251 -0.01913163  0.00321374  0.11219989
## 3     CRM -0.93417722 -0.19628647 -0.04788906 -0.04935839  0.06666667
##        x.Max.
## 1  1.00000000
## 2  0.47621319
## 3  1.00000000
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  six months"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  65  81  71 
## [1] ""
## [1] "Summary Statistics for variable  geometry_changes_share"
##   Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean    x.3rd Qu.
## 1      CG -0.950000000 -0.095173417  0.022672247  0.032608779  0.166666667
## 2     CFM -0.693057430 -0.106353887 -0.004795512 -0.007835090  0.072508192
## 3     CRM -0.601528925 -0.128536656 -0.004433012  0.002353978  0.130519481
##         x.Max.
## 1  0.744186047
## 2  0.743411928
## 3  0.489584712
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  one year"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  59  68  58 
## [1] ""
## [1] "Summary Statistics for variable  geometry_changes_share"
##   Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean    x.3rd Qu.
## 1      CG -0.633333333 -0.184419912 -0.081027668 -0.052200865  0.065193510
## 2     CFM -0.544627077 -0.057868778 -0.001710282 -0.003644488  0.071265967
## 3     CRM -0.762116716 -0.210131243  0.010269366 -0.036683273  0.121573068
##         x.Max.
## 1  0.516129032
## 2  0.526785714
## 3  0.834754050
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  two years"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  63  63  49 
## [1] ""
## [1] "Summary Statistics for variable  geometry_changes_share"
##   Group.1      x.Min.   x.1st Qu.    x.Median      x.Mean   x.3rd Qu.
## 1      CG -0.80974415 -0.27422279 -0.03789800 -0.05584130  0.17824850
## 2     CFM -0.99567100 -0.10947165 -0.02770149 -0.01327344  0.14752621
## 3     CRM -0.52737002 -0.20104452  0.00976335 -0.01542560  0.18813920
##        x.Max.
## 1  0.55205950
## 2  0.50577300
## 3  0.47824549
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "========================================================================"
## [1] "RESULTS FOR VARIABLE edit_diversity"
## [1] "========================================================================"
## [1] ""
## [1] ""

## [1] ""

## [1] ""
## [1] "Boxplot on contributors only: "

## [1] ""
## [1] ""
## [1] "Time frame:  one month"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  32  84  61 
## [1] ""
## [1] "Summary Statistics for variable  edit_diversity"
##   Group.1      x.Min.   x.1st Qu.    x.Median      x.Mean   x.3rd Qu.
## 1      CG -3.14376227 -0.33263312  0.00000000 -0.06971464  0.21702523
## 2     CFM -1.70786050 -0.20065577  0.11182827  0.13851699  0.49003247
## 3     CRM -1.79803858 -0.66797221 -0.23301179 -0.04203377  0.50266155
##        x.Max.
## 1  2.51559359
## 2  2.16831026
## 3  2.38211647
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  six months"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  65  81  71 
## [1] ""
## [1] "Summary Statistics for variable  edit_diversity"
##   Group.1      x.Min.   x.1st Qu.    x.Median      x.Mean   x.3rd Qu.
## 1      CG -1.92839993 -0.61447798 -0.00742398 -0.04457572  0.28417065
## 2     CFM -2.29465344 -0.11925552  0.10436179  0.11652432  0.55010868
## 3     CRM -1.29027001 -0.20472745  0.24561491  0.26379599  0.68525977
##        x.Max.
## 1  2.68289115
## 2  2.11140843
## 3  2.16026510
## [1] ""
## [1] ""
## [1] "edit_diversity is significantly influenced by an event for six months"
## [1] ""
## [1] ""
## [1] "Pairwise comparison: "
##             CG       CFM
## CFM 0.12476388        NA
## CRM 0.03047654 0.2942714
## [1] "Cohends d for effect size of the CRM on edit_diversity :"
## 
## Cohen's d
## 
## d estimate: -0.3693338 (small)
## 95 percent confidence interval:
##       lower       upper 
## -0.71173544 -0.02693207 
## [1] ""
## [1] "N:"
## [1] 71
## [1] ""
## [1] "N:"
## [1] 71
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  one year"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  59  68  58 
## [1] ""
## [1] "Summary Statistics for variable  edit_diversity"
##   Group.1      x.Min.   x.1st Qu.    x.Median      x.Mean   x.3rd Qu.
## 1      CG -2.31165349 -0.94953461 -0.45836025 -0.44715086  0.06208216
## 2     CFM -2.19914408 -0.45970259 -0.15149802 -0.12113047  0.22091517
## 3     CRM -2.20689119 -0.86699488 -0.14225759 -0.22573654  0.38928102
##        x.Max.
## 1  2.29123048
## 2  1.66113036
## 3  1.65911820
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  two years"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  63  63  49 
## [1] ""
## [1] "Summary Statistics for variable  edit_diversity"
##   Group.1      x.Min.   x.1st Qu.    x.Median      x.Mean   x.3rd Qu.
## 1      CG -2.97325576 -1.09017640 -0.25792778 -0.38237963  0.31977482
## 2     CFM -2.60925273 -0.59504122 -0.03212027 -0.19961145  0.26105365
## 3     CRM -1.95919616 -0.59864993 -0.03368777 -0.05340236  0.38381580
##        x.Max.
## 1  1.97850957
## 2  2.16899146
## 3  2.54742710
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "========================================================================"
## [1] "RESULTS FOR VARIABLE edit_complexity"
## [1] "========================================================================"
## [1] ""
## [1] ""

## [1] ""

## [1] ""
## [1] "Boxplot on contributors only: "

## [1] ""
## [1] ""
## [1] "Time frame:  one month"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  32  84  61 
## [1] ""
## [1] "Summary Statistics for variable  edit_complexity"
##   Group.1      x.Min.   x.1st Qu.    x.Median      x.Mean   x.3rd Qu.
## 1      CG -2.00000000  0.00000000  0.00000000  0.00000000  0.00000000
## 2     CFM -2.00000000  0.00000000  0.00000000 -0.03571429  0.00000000
## 3     CRM -1.00000000  0.00000000  0.00000000  0.01639344  0.00000000
##        x.Max.
## 1  3.00000000
## 2  2.00000000
## 3  1.00000000
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  six months"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  65  81  71 
## [1] ""
## [1] "Summary Statistics for variable  edit_complexity"
##   Group.1      x.Min.   x.1st Qu.    x.Median      x.Mean   x.3rd Qu.
## 1      CG -3.00000000  0.00000000  0.00000000 -0.03076923  0.00000000
## 2     CFM -1.00000000  0.00000000  0.00000000 -0.11111111  0.00000000
## 3     CRM -1.00000000  0.00000000  0.00000000  0.08450704  0.00000000
##        x.Max.
## 1  3.00000000
## 2  1.00000000
## 3  3.00000000
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  one year"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  59  68  58 
## [1] ""
## [1] "Summary Statistics for variable  edit_complexity"
##   Group.1      x.Min.   x.1st Qu.    x.Median      x.Mean   x.3rd Qu.
## 1      CG -2.00000000  0.00000000  0.00000000 -0.08474576  0.00000000
## 2     CFM -2.00000000  0.00000000  0.00000000  0.11764706  0.00000000
## 3     CRM -4.00000000  0.00000000  0.00000000 -0.05172414  0.00000000
##        x.Max.
## 1  3.00000000
## 2  4.00000000
## 3  1.00000000
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  two years"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  63  63  49 
## [1] ""
## [1] "Summary Statistics for variable  edit_complexity"
##   Group.1      x.Min.   x.1st Qu.    x.Median      x.Mean   x.3rd Qu.
## 1      CG -4.00000000  0.00000000  0.00000000 -0.01587302  0.00000000
## 2     CFM -1.00000000  0.00000000  0.00000000  0.07936508  0.00000000
## 3     CRM -1.00000000  0.00000000  0.00000000  0.22448980  1.00000000
##        x.Max.
## 1  2.00000000
## 2  3.00000000
## 3  3.00000000
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "========================================================================"
## [1] "RESULTS FOR VARIABLE quality"
## [1] "========================================================================"
## [1] ""
## [1] ""

## [1] ""

## [1] ""
## [1] "Boxplot on contributors only: "

## [1] ""
## [1] ""
## [1] "Time frame:  one month"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  32  84  61 
## [1] ""
## [1] "Summary Statistics for variable  quality"
##   Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean    x.3rd Qu.
## 1      CG -1.000000000 -0.065218026  0.000000000 -0.015124392  0.092072511
## 2     CFM -1.166666667 -0.069919308 -0.002365963 -0.020397315  0.067905862
## 3     CRM -0.895794099 -0.120332850 -0.003859687 -0.017884805  0.128205128
##         x.Max.
## 1  1.000000000
## 2  0.706842165
## 3  0.771095571
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  six months"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  65  81  71 
## [1] ""
## [1] "Summary Statistics for variable  quality"
##   Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean    x.3rd Qu.
## 1      CG -1.187500000 -0.104353011 -0.029221298 -0.044264684  0.030350877
## 2     CFM -0.500000000 -0.123188406 -0.017543860 -0.009974484  0.038601375
## 3     CRM -0.664615385 -0.167036871 -0.006729900 -0.046344662  0.070638974
##         x.Max.
## 1  1.000000000
## 2  0.837003463
## 3  0.603795967
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  one year"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  59  68  58 
## [1] ""
## [1] "Summary Statistics for variable  quality"
##   Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean    x.3rd Qu.
## 1      CG -0.382344828 -0.067125720  0.000000000  0.012860648  0.081439394
## 2     CFM -0.664524242 -0.076776338 -0.018462545 -0.004801161  0.075952388
## 3     CRM -0.739700375 -0.186136694 -0.029829113 -0.077379566  0.128422803
##         x.Max.
## 1  0.750000000
## 2  0.501186107
## 3  0.568347339
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  two years"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  63  63  49 
## [1] ""
## [1] "Summary Statistics for variable  quality"
##   Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean    x.3rd Qu.
## 1      CG -0.545454545 -0.072960078 -0.013888889 -0.000685024  0.086890497
## 2     CFM -0.354379468 -0.127365097 -0.009659735  0.001172579  0.052231745
## 3     CRM -0.780626781 -0.100085218 -0.010303311  0.047495898  0.115677928
##         x.Max.
## 1  0.336649802
## 2  0.783275329
## 3  1.000000000
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "========================================================================"
## [1] "RESULTS FOR VARIABLE element_density"
## [1] "========================================================================"
## [1] ""
## [1] ""

## [1] ""

## [1] ""
## [1] "Boxplot on contributors only: "

## [1] ""
## [1] ""
## [1] "Time frame:  six months"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  65  81  71 
## [1] ""
## [1] "Summary Statistics for variable  element_density"
##   Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean    x.3rd Qu.
## 1      CG  -3.29214447  -0.83129085  -0.36757852  -0.30576359  -0.02316485
## 2     CFM -15.46749935  -1.07873555  -0.26228247  -0.64209874   0.11038270
## 3     CRM -14.43749929  -0.53146193  -0.06548427  -0.55009480   0.02589848
##         x.Max.
## 1   9.45304035
## 2   8.16383192
## 3   1.08933334
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  one year"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  59  68  58 
## [1] ""
## [1] "Summary Statistics for variable  element_density"
##   Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean    x.3rd Qu.
## 1      CG -16.68428915  -1.37243995  -0.42650976  -1.07554231  -0.08482411
## 2     CFM -18.72012236  -2.22089700  -0.70673807  -1.72473370  -0.18716077
## 3     CRM -20.60769904  -1.09811668  -0.53159468  -1.21595118  -0.22564655
##         x.Max.
## 1   8.65281447
## 2   2.17562000
## 3   0.24634054
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  two years"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  63  63  49 
## [1] ""
## [1] "Summary Statistics for variable  element_density"
##   Group.1        x.Min.     x.1st Qu.      x.Median        x.Mean
## 1      CG -34.381616769  -1.450171073  -0.272084952  -1.384673511
## 2     CFM -57.156974358  -2.759446417  -1.381334674  -2.985021771
## 3     CRM -23.745956068  -1.181449585  -0.470173414  -1.517775519
##       x.3rd Qu.        x.Max.
## 1   0.033647901  11.735189891
## 2  -0.444256373   0.687898359
## 3   0.001454791   1.368294918
## [1] ""
## [1] ""
## [1] "element_density is significantly influenced by an event for two years"
## [1] ""
## [1] ""
## [1] "Pairwise comparison: "
##              CG         CFM
## CFM 0.001595262          NA
## CRM 0.626390168 0.003174734
## [1] "Cohends d for effect size of the CFM on element_density :"
## 
## Cohen's d
## 
## d estimate: 0.2546607 (small)
## 95 percent confidence interval:
##       lower       upper 
## -0.09942244  0.60874376 
## [1] ""
## [1] "N:"
## [1] 63
## [1] "N:"
##          low income lower middle income upper middle income 
##                   2                   5                  13 
##         high income 
##                  43 
## [1] ""
## [1] "Summary Statistics: "
##               Group.1      x.Min.   x.1st Qu.    x.Median      x.Mean
## 1          low income  -2.5519636  -2.1373135  -1.7226635  -1.7226635
## 2 lower middle income -11.3465794  -2.4191744  -1.7355563  -3.7126154
## 3 upper middle income  -5.2388697  -0.8676909  -0.3933291  -0.9849859
## 4         high income -57.1569744  -3.1145624  -1.5666489  -3.5637942
##     x.3rd Qu.      x.Max.
## 1  -1.3080135  -0.8933634
## 2  -1.6804321  -1.3813347
## 3  -0.1804580   0.0531250
## 4  -0.5689873   0.6878984
## [1] ""
## [1] "N:"
##        Japanese Latin  American         Western           Other 
##              10              15              32               6 
## [1] ""
## [1] "Summary Statistics: "
##           Group.1      x.Min.   x.1st Qu.    x.Median      x.Mean
## 1        Japanese  -6.3616220  -2.7729867  -0.8733865  -1.6889248
## 2 Latin  American  -3.4049810  -2.0741512  -0.5649409  -1.1434911
## 3         Western -57.1569744  -4.2490632  -1.6511026  -4.4410230
## 4           Other  -5.2388697  -2.5187663  -1.6434326  -1.9836702
##     x.3rd Qu.      x.Max.
## 1  -0.4163755   0.4594882
## 2  -0.1432251   0.0531250
## 3  -0.8091837   0.6878984
## 4  -0.6417095  -0.2579405
## [1] ""
## [1] "Cohends d for effect size between CRM and CFM on element_density :"
## 
## Cohen's d
## 
## d estimate: -0.2384911 (small)
## 95 percent confidence interval:
##      lower      upper 
## -0.6172888  0.1403066 
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "========================================================================"
## [1] "RESULTS FOR VARIABLE tag_density"
## [1] "========================================================================"
## [1] ""
## [1] ""

## [1] ""

## [1] ""
## [1] "Boxplot on contributors only: "

## [1] ""
## [1] ""
## [1] "Time frame:  six months"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  65  81  71 
## [1] ""
## [1] "Summary Statistics for variable  tag_density"
##   Group.1      x.Min.   x.1st Qu.    x.Median      x.Mean   x.3rd Qu.
## 1      CG -3.52797725 -0.62271885 -0.02610442 -0.15402765  0.63270945
## 2     CFM -2.54876812 -0.31571610  0.04460608  0.06445798  0.34092268
## 3     CRM -2.55555556 -0.38695212 -0.05395488  0.05053628  0.46143363
##        x.Max.
## 1  2.33502024
## 2  5.48576850
## 3  2.73568954
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  one year"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  59  68  58 
## [1] ""
## [1] "Summary Statistics for variable  tag_density"
##   Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean    x.3rd Qu.
## 1      CG -2.716878843 -0.345849735  0.061705533 -0.043489349  0.505491787
## 2     CFM -2.397692570 -0.333023866  0.045753086  0.007608159  0.413475002
## 3     CRM -3.087121693 -0.494628332  0.078516192  0.076043562  0.574728753
##         x.Max.
## 1  2.273569438
## 2  1.368481825
## 3  3.622892445
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  two years"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  63  63  49 
## [1] ""
## [1] "Summary Statistics for variable  tag_density"
##   Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean    x.3rd Qu.
## 1      CG -3.078385668 -0.259308989  0.233623934  0.325730037  0.755341773
## 2     CFM -2.535835914 -0.262794362  0.063003393  0.089603186  0.538425875
## 3     CRM -3.224390244 -0.352708960 -0.002886209 -0.080390725  0.425820221
##         x.Max.
## 1  3.637640449
## 2  2.631912553
## 3  2.547085764
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "========================================================================"
## [1] "RESULTS FOR VARIABLE user_density"
## [1] "========================================================================"
## [1] ""
## [1] ""

## [1] ""

## [1] ""
## [1] "Boxplot on contributors only: "

## [1] ""
## [1] ""
## [1] "Time frame:  six months"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  65  81  71 
## [1] ""
## [1] "Summary Statistics for variable  user_density"
##   Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean    x.3rd Qu.
## 1      CG -3.743259804 -0.504462590 -0.191673303 -0.422027551  0.037418996
## 2     CFM -2.278513961 -0.274445326 -0.137547934 -0.120334526  0.079287124
## 3     CRM -5.136405465 -0.386252194  0.008603136 -0.200938850  0.329697618
##         x.Max.
## 1  0.926498254
## 2  3.120493359
## 3  5.142857143
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  one year"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  59  68  58 
## [1] ""
## [1] "Summary Statistics for variable  user_density"
##   Group.1      x.Min.   x.1st Qu.    x.Median      x.Mean   x.3rd Qu.
## 1      CG -3.38389262 -0.57339665 -0.24726588 -0.43658630 -0.08191022
## 2     CFM -1.11247740 -0.43061260 -0.20168634 -0.20486311  0.03607641
## 3     CRM -5.21113625 -0.45345691 -0.16735498 -0.23558675  0.17095040
##        x.Max.
## 1  2.33021807
## 2  0.76356186
## 3  3.22822300
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  two years"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  63  63  49 
## [1] ""
## [1] "Summary Statistics for variable  user_density"
##   Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean    x.3rd Qu.
## 1      CG -1.923611111 -0.601714528 -0.205572242 -0.008933829  0.253646732
## 2     CFM -2.434578786 -0.670324271 -0.444121799 -0.486754114 -0.188410511
## 3     CRM -6.454545455 -1.110122620 -0.547407977 -0.677364394 -0.109672038
##         x.Max.
## 1  2.926966292
## 2  0.383059082
## 3  3.604790419
## [1] ""
## [1] ""
## [1] "user_density is significantly influenced by an event for two years"
## [1] ""
## [1] ""
## [1] "Pairwise comparison: "
##              CG       CFM
## CFM 0.004854688        NA
## CRM 0.004854688 0.3215774
## [1] "Cohends d for effect size of the CFM on user_density :"
## 
## Cohen's d
## 
## d estimate: 0.6465855 (medium)
## 95 percent confidence interval:
##     lower     upper 
## 0.2848315 1.0083394 
## [1] ""
## [1] "N:"
## [1] 63
## [1] "N:"
##          low income lower middle income upper middle income 
##                   2                   5                  13 
##         high income 
##                  43 
## [1] ""
## [1] "Summary Statistics: "
##               Group.1      x.Min.   x.1st Qu.    x.Median      x.Mean
## 1          low income -0.89674299 -0.78533556 -0.67392814 -0.67392814
## 2 lower middle income -0.59137921 -0.58556936 -0.46615829 -0.43208258
## 3 upper middle income -2.43457879 -0.85615296 -0.52840389 -0.75124323
## 4         high income -1.19368610 -0.62777014 -0.33753421 -0.40444368
##     x.3rd Qu.      x.Max.
## 1 -0.56252071 -0.45111328
## 2 -0.41866241 -0.09864363
## 3 -0.42069234  0.38305908
## 4 -0.16068357  0.25732578
## [1] ""
## [1] "N:"
##        Japanese Latin  American         Western           Other 
##              10              15              32               6 
## [1] ""
## [1] "Summary Statistics: "
##           Group.1      x.Min.   x.1st Qu.    x.Median      x.Mean
## 1        Japanese -0.65519863 -0.44210437 -0.25420747 -0.30557848
## 2 Latin  American -2.43457879 -0.94329239 -0.79464081 -0.88826612
## 3         Western -1.19368610 -0.53170688 -0.35619404 -0.39644873
## 4           Other -0.59137921 -0.50908124 -0.43590281 -0.26656219
##     x.3rd Qu.      x.Max.
## 1 -0.16680404 -0.03821709
## 2 -0.51431268 -0.06484325
## 3 -0.15584845  0.25732578
## 4 -0.09830573  0.38305908
## [1] ""
## [1] ""
## [1] "user_density is significantly influenced by at least one culture for CFM with p= 0.00497984007002043"
## [1] ""
## [1] "Pairwise comparison: "
##                    Japanese Latin  American   Western
## Latin  American 0.006723972              NA        NA
## Western         0.797076719     0.006723972        NA
## Other           0.957792208     0.036709421 0.8881113

## NULL
## [1] ""
## [1] "Cohends d for effect size of the CRM on user_density :"
## 
## Cohen's d
## 
## d estimate: 0.5177255 (medium)
## 95 percent confidence interval:
##    lower    upper 
## 0.134072 0.901379 
## [1] ""
## [1] "N:"
## [1] 49
## [1] ""
## [1] "N:"
## [1] 49
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "========================================================================"
## [1] "RESULTS FOR VARIABLE area_diversity"
## [1] "========================================================================"
## [1] ""
## [1] ""

## [1] ""

## [1] ""
## [1] "Boxplot on contributors only: "

## [1] ""
## [1] ""
## [1] "Time frame:  six months"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  65  81  71 
## [1] ""
## [1] "Summary Statistics for variable  area_diversity"
##   Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean    x.3rd Qu.
## 1      CG -1.842857006 -0.341359788 -0.022531173 -0.179935160  0.167984308
## 2     CFM -1.422207457 -0.173104420  0.003082655 -0.021360185  0.201119421
## 3     CRM -1.362306597 -0.108057654  0.084905339  0.085573734  0.310994546
##         x.Max.
## 1  0.630932466
## 2  1.195938631
## 3  1.158045511
## [1] ""
## [1] ""
## [1] "area_diversity is significantly influenced by an event for six months"
## [1] ""
## [1] ""
## [1] "Pairwise comparison: "
##             CG       CFM
## CFM 0.19111535        NA
## CRM 0.01993412 0.1516106
## [1] "Cohends d for effect size of the CRM on area_diversity :"
## 
## Cohen's d
## 
## d estimate: -0.519696 (medium)
## 95 percent confidence interval:
##      lower      upper 
## -0.8648936 -0.1744984 
## [1] ""
## [1] "N:"
## [1] 71
## [1] ""
## [1] "N:"
## [1] 71
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  one year"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  59  68  58 
## [1] ""
## [1] "Summary Statistics for variable  area_diversity"
##   Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean    x.3rd Qu.
## 1      CG -1.554703226 -0.176157888  0.005653514 -0.034644440  0.243379302
## 2     CFM -1.135271729 -0.128462118  0.058205587  0.030616886  0.233352918
## 3     CRM -1.348208938 -0.337359188  0.029058086 -0.023853846  0.264225391
##         x.Max.
## 1  0.903456940
## 2  0.734499021
## 3  1.290499385
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  two years"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  63  63  49 
## [1] ""
## [1] "Summary Statistics for variable  area_diversity"
##   Group.1      x.Min.   x.1st Qu.    x.Median      x.Mean   x.3rd Qu.
## 1      CG -1.79857415 -0.11932157  0.11664621  0.13975220  0.39377761
## 2     CFM -0.68532364 -0.06681390  0.06052850  0.08145187  0.22285255
## 3     CRM -1.72140025 -0.46433953  0.00395659 -0.07194113  0.18996466
##        x.Max.
## 1  2.08883428
## 2  0.99696835
## 3  1.47322710
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "========================================================================"
## [1] "RESULTS FOR VARIABLE economic_distance"
## [1] "========================================================================"
## [1] ""
## [1] ""

## [1] ""

## [1] ""
## [1] "Boxplot on contributors only: "

## [1] ""
## [1] ""
## [1] "Time frame:  one month"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  32  84  61 
## [1] ""
## [1] "Summary Statistics for variable  economic_distance"
##   Group.1      x.Min.   x.1st Qu.    x.Median      x.Mean   x.3rd Qu.
## 1      CG -1.00000000  0.00000000  0.00000000 -0.02259419  0.00000000
## 2     CFM -1.00000000  0.00000000  0.00000000 -0.02536913  0.00000000
## 3     CRM -1.00000000 -0.04826418  0.00000000  0.03397207  0.16648595
##        x.Max.
## 1  0.61818182
## 2  0.02313285
## 3  1.00000000
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  six months"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  65  81  71 
## [1] ""
## [1] "Summary Statistics for variable  economic_distance"
##   Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean    x.3rd Qu.
## 1      CG -0.885364543  0.000000000  0.000000000 -0.021912483  0.000000000
## 2     CFM -1.000000000  0.000000000  0.000000000  0.013984017  0.003576595
## 3     CRM -0.961538462 -0.076697491  0.000000000  0.014205377  0.005290329
##         x.Max.
## 1  0.663155721
## 2  0.804228051
## 3  1.000000000
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  one year"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  59  68  58 
## [1] ""
## [1] "Summary Statistics for variable  economic_distance"
##   Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean    x.3rd Qu.
## 1      CG -0.599595843  0.000000000  0.000000000 -0.019093086  0.000000000
## 2     CFM -0.871701331  0.000000000  0.000000000  0.003318972  0.008467907
## 3     CRM -1.000000000 -0.037265619  0.000000000  0.107274073  0.118770311
##         x.Max.
## 1  0.607142857
## 2  1.000000000
## 3  1.000000000
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  two years"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  63  63  49 
## [1] ""
## [1] "Summary Statistics for variable  economic_distance"
##   Group.1        x.Min.     x.1st Qu.      x.Median        x.Mean
## 1      CG -0.9847328244  0.0000000000  0.0000000000  0.0011126034
## 2     CFM -0.6832061069 -0.0004781185  0.0000000000  0.0296240086
## 3     CRM -0.9885386819 -0.0573461320  0.0087719298  0.1378210161
##       x.3rd Qu.        x.Max.
## 1  0.0000000000  0.4615555556
## 2  0.0116528541  0.9280936455
## 3  0.3804379730  1.0000000000
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "========================================================================"
## [1] "RESULTS FOR VARIABLE cultural_distance"
## [1] "========================================================================"
## [1] ""
## [1] ""

## [1] ""

## [1] ""
## [1] "Boxplot on contributors only: "

## [1] ""
## [1] ""
## [1] "Time frame:  one month"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  32  84  61 
## [1] ""
## [1] "Summary Statistics for variable  cultural_distance"
##   Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean    x.3rd Qu.
## 1      CG -1.000000000  0.000000000  0.000000000 -0.022475459  0.000000000
## 2     CFM -1.000000000  0.000000000  0.000000000 -0.012749383  0.000000000
## 3     CRM -1.000000000 -0.075633015  0.000000000 -0.005261958  0.139488737
##         x.Max.
## 1  0.618181818
## 2  0.497862030
## 3  1.000000000
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  six months"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  65  81  71 
## [1] ""
## [1] "Summary Statistics for variable  cultural_distance"
##   Group.1      x.Min.   x.1st Qu.    x.Median      x.Mean   x.3rd Qu.
## 1      CG -0.82900480  0.00000000  0.00000000 -0.01473030  0.00000000
## 2     CFM -1.00000000  0.00000000  0.00000000  0.01973918  0.00911800
## 3     CRM -0.96153846 -0.05213316  0.00000000  0.03979331  0.02924433
##        x.Max.
## 1  0.65695993
## 2  1.00000000
## 3  1.00000000
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  one year"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  59  68  58 
## [1] ""
## [1] "Summary Statistics for variable  cultural_distance"
##   Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean    x.3rd Qu.
## 1      CG -0.599595843  0.000000000  0.000000000 -0.014542715  0.000000000
## 2     CFM -0.721951220  0.000000000  0.000000000  0.019736584  0.007713745
## 3     CRM -1.000000000 -0.037265619  0.000000000  0.094057709  0.118770311
##         x.Max.
## 1  0.607142857
## 2  1.000000000
## 3  1.000000000
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  two years"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  63  63  49 
## [1] ""
## [1] "Summary Statistics for variable  cultural_distance"
##   Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean    x.3rd Qu.
## 1      CG -0.984732824  0.000000000  0.000000000 -0.013708634  0.000000000
## 2     CFM -0.521682044 -0.033870080  0.000000000  0.001078209  0.008305939
## 3     CRM -0.988538682 -0.015303721  0.027253669  0.155215746  0.293630436
##         x.Max.
## 1  0.461555556
## 2  0.928093645
## 3  1.000000000
## [1] ""
## [1] ""
## [1] "cultural_distance is significantly influenced by an event for two years"
## [1] ""
## [1] ""
## [1] "Pairwise comparison: "
##             CG        CFM
## CFM 0.75210400         NA
## CRM 0.02889855 0.02889855
## [1] "Cohends d for effect size of the CRM on cultural_distance :"
## 
## Cohen's d
## 
## d estimate: -0.5716814 (medium)
## 95 percent confidence interval:
##      lower      upper 
## -0.9566757 -0.1866871 
## [1] ""
## [1] "N:"
## [1] 49
## [1] ""
## [1] "N:"
## [1] 49
## [1] ""
## [1] "Cohends d for effect size between CRM and CFM on cultural_distance :"
## 
## Cohen's d
## 
## d estimate: -0.5092217 (medium)
## 95 percent confidence interval:
##      lower      upper 
## -0.8926756 -0.1257678 
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "========================================================================"
## [1] "RESULTS FOR VARIABLE population_density_distance"
## [1] "========================================================================"
## [1] ""
## [1] ""

## [1] ""

## [1] ""
## [1] "Boxplot on contributors only: "
## [1] ""
## [1] ""
## [1] "Time frame:  one month"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  32  84  61 
## [1] ""
## [1] "Summary Statistics for variable  population_density_distance"
##   Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean    x.3rd Qu.
## 1      CG -1.000000000 -0.019534413  0.000000000  0.066822176  0.221725787
## 2     CFM -1.000000000 -0.087117344  0.009498418  0.079289501  0.173762241
## 3     CRM -1.000000000 -0.200000000  0.000000000 -0.034907111  0.070593735
##         x.Max.
## 1  1.000000000
## 2  0.916335979
## 3  1.000000000
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  six months"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  65  81  71 
## [1] ""
## [1] "Summary Statistics for variable  population_density_distance"
##   Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean    x.3rd Qu.
## 1      CG -0.947112534 -0.015337049  0.000000000  0.060628108  0.165128205
## 2     CFM -0.952210275 -0.102382144  0.001862814  0.064503876  0.255883611
## 3     CRM -0.861538462 -0.029429799  0.049266507  0.171580350  0.437556376
##         x.Max.
## 1  1.000000000
## 2  1.000000000
## 3  1.000000000
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  one year"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  59  68  58 
## [1] ""
## [1] "Summary Statistics for variable  population_density_distance"
##   Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean    x.3rd Qu.
## 1      CG -0.956326988 -0.111903977  0.000000000 -0.016065088  0.054112024
## 2     CFM -0.965008503 -0.099971057  0.005304855  0.003651063  0.132760980
## 3     CRM -1.000000000 -0.042023594  0.125526269  0.161710787  0.487744362
##         x.Max.
## 1  0.909090909
## 2  0.715638818
## 3  1.000000000
## [1] ""
## [1] ""
## [1] "population_density_distance is significantly influenced by an event for one year"
## [1] ""
## [1] ""
## [1] "Pairwise comparison: "
##             CG       CFM
## CFM 0.40329589        NA
## CRM 0.01013738 0.0221628
## [1] "Cohends d for effect size of the CRM on population_density_distance :"
## 
## Cohen's d
## 
## d estimate: -0.4742209 (small)
## 95 percent confidence interval:
##      lower      upper 
## -0.8455977 -0.1028442 
## [1] ""
## [1] "N:"
## [1] 58
## [1] ""
## [1] "N:"
## [1] 58
## [1] ""
## [1] "Analyses of the effect of the distance to the Region mapped during the event for CRM"
## Warning in xy.coords(x, y, xlabel, ylabel, log): 17 x values <= 0 omitted
## from logarithmic plot

## NULL

## NULL
## 
## Call:
## lm(formula = variable2 ~ classes2)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -1.06831 -0.25553  0.09345  0.25693  0.73195 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)   
## (Intercept) -0.03155    0.07667  -0.412   0.6822   
## classes2     0.09987    0.02902   3.441   0.0011 **
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.3975 on 56 degrees of freedom
## Multiple R-squared:  0.1746, Adjusted R-squared:  0.1598 
## F-statistic: 11.84 on 1 and 56 DF,  p-value: 0.001101
## 
## [1] ""
## [1] "Cohends d for effect size between CRM and CFM on population_density_distance :"
## 
## Cohen's d
## 
## d estimate: -0.422367 (small)
## 95 percent confidence interval:
##       lower       upper 
## -0.78003764 -0.06469641 
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  two years"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  63  63  49 
## [1] ""
## [1] "Summary Statistics for variable  population_density_distance"
##   Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean    x.3rd Qu.
## 1      CG -1.000000000 -0.087653678  0.000000000  0.014547688  0.127355576
## 2     CFM -1.000000000 -0.108849945 -0.003737379  0.007075097  0.154065317
## 3     CRM -0.576612903 -0.009165103  0.072321737  0.107282666  0.255679571
##         x.Max.
## 1  0.941176471
## 2  0.916666667
## 3  1.000000000
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "========================================================================"
## [1] "RESULTS FOR VARIABLE physical_geography_distance"
## [1] "========================================================================"
## [1] ""
## [1] ""

## [1] ""

## [1] ""
## [1] "Boxplot on contributors only: "

## [1] ""
## [1] ""
## [1] "Time frame:  one month"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  32  84  61 
## [1] ""
## [1] "Summary Statistics for variable  physical_geography_distance"
##   Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean    x.3rd Qu.
## 1      CG -1.000000000  0.000000000  0.000000000  0.023529533  0.004326411
## 2     CFM -1.000000000  0.000000000  0.000000000  0.013964297  0.014078705
## 3     CRM -1.000000000 -0.057578323  0.000000000  0.010796674  0.079539407
##         x.Max.
## 1  1.000000000
## 2  0.992465016
## 3  1.000000000
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  six months"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  65  81  71 
## [1] ""
## [1] "Summary Statistics for variable  physical_geography_distance"
##   Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean    x.3rd Qu.
## 1      CG -0.800000000 -0.005816675  0.000000000 -0.007519380  0.012432432
## 2     CFM -0.404522809 -0.015833920  0.000000000  0.049127437  0.042527565
## 3     CRM -0.961538462 -0.010731333  0.000000000  0.084790851  0.079993147
##         x.Max.
## 1  1.000000000
## 2  0.941666667
## 3  1.000000000
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  one year"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  59  68  58 
## [1] ""
## [1] "Summary Statistics for variable  physical_geography_distance"
##   Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean    x.3rd Qu.
## 1      CG -1.000000000 -0.001526328  0.000000000  0.003429070  0.000000000
## 2     CFM -0.643410853 -0.021169292  0.000000000  0.008600134  0.044807436
## 3     CRM -1.000000000 -0.004314616  0.017614259  0.134813158  0.304305283
##         x.Max.
## 1  0.607142857
## 2  1.000000000
## 3  1.000000000
## [1] ""
## [1] ""
## [1] "physical_geography_distance is significantly influenced by an event for one year"
## [1] ""
## [1] ""
## [1] "Pairwise comparison: "
##             CG        CFM
## CFM 0.64921212         NA
## CRM 0.03970285 0.03970285
## [1] "Cohends d for effect size of the CRM on physical_geography_distance :"
## 
## Cohen's d
## 
## d estimate: -0.4423525 (small)
## 95 percent confidence interval:
##       lower       upper 
## -0.81306923 -0.07163571 
## [1] ""
## [1] "N:"
## [1] 58
## [1] ""
## [1] "N:"
## [1] 58
## [1] ""
## [1] "Cohends d for effect size between CRM and CFM on physical_geography_distance :"
## 
## Cohen's d
## 
## d estimate: -0.4239085 (small)
## 95 percent confidence interval:
##       lower       upper 
## -0.78160750 -0.06620957 
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  two years"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  63  63  49 
## [1] ""
## [1] "Summary Statistics for variable  physical_geography_distance"
##   Group.1        x.Min.     x.1st Qu.      x.Median        x.Mean
## 1      CG -0.9675324675 -0.0036943665  0.0000000000  0.0121488346
## 2     CFM -1.0000000000 -0.0353591199  0.0000000000  0.0453609888
## 3     CRM -0.8715336729 -0.0570564449  0.0138623998  0.1438123693
##       x.3rd Qu.        x.Max.
## 1  0.0008741259  1.0000000000
## 2  0.1477890471  0.7879943625
## 3  0.3248407282  1.0000000000
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "========================================================================"
## [1] "RESULTS FOR VARIABLE comment_size"
## [1] "========================================================================"
## [1] ""
## [1] ""

## [1] ""

## [1] ""
## [1] "Boxplot on contributors only: "

## [1] ""
## [1] ""
## [1] "Time frame:  one month"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  32  84  61 
## [1] ""
## [1] "Summary Statistics for variable  comment_size"
##   Group.1      x.Min.   x.1st Qu.    x.Median      x.Mean   x.3rd Qu.
## 1      CG -3.00000000 -0.01879540  0.09770115  0.73148633  1.37500000
## 2     CFM -5.23958333 -0.38529641  0.00000000 -0.12328100  0.29182692
## 3     CRM -5.37500000 -0.80307692  0.08943089 -0.14552938  0.57547170
##        x.Max.
## 1  6.87323944
## 2  5.24921630
## 3 11.06666667
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  six months"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  65  81  71 
## [1] ""
## [1] "Summary Statistics for variable  comment_size"
##   Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean    x.3rd Qu.
## 1      CG  -8.54545455  -0.16017316   0.27026175   0.18971503   1.20833333
## 2     CFM -10.66666667  -0.31406749   0.01845170  -0.04413231   0.48208617
## 3     CRM  -3.23333333  -0.27924048   0.09821429   0.45928010   0.74730041
##         x.Max.
## 1   4.58914729
## 2   7.06060606
## 3   5.50000000
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  one year"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  59  68  58 
## [1] ""
## [1] "Summary Statistics for variable  comment_size"
##   Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean    x.3rd Qu.
## 1      CG -5.712121212 -0.166666667  0.437969925  0.768838161  1.307474618
## 2     CFM -6.650793651 -0.325924000  0.009915399 -0.058749366  0.403993444
## 3     CRM -4.217105263 -0.306406473  0.118842567  0.738354228  0.749631211
##         x.Max.
## 1  8.000000000
## 2  2.023569024
## 3 13.981308411
## [1] ""
## [1] ""
## [1] "comment_size is significantly influenced by an event for one year"
## [1] ""
## [1] ""
## [1] "Pairwise comparison: "
##             CG       CFM
## CFM 0.02973204        NA
## CRM 0.27829241 0.2782924
## [1] "Cohends d for effect size of the CFM on comment_size :"
## 
## Cohen's d
## 
## d estimate: 0.443159 (small)
## 95 percent confidence interval:
##     lower     upper 
## 0.0867615 0.7995564 
## [1] ""
## [1] "N:"
## [1] 68
## [1] "N:"
##          low income lower middle income upper middle income 
##                   2                   5                  15 
##         high income 
##                  46 
## [1] ""
## [1] "Summary Statistics: "
##               Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean
## 1          low income -2.099391481 -1.593007680 -1.086623880 -1.086623880
## 2 lower middle income -0.590613834 -0.357751259 -0.113398204 -0.163729006
## 3 upper middle income -1.317092723  0.009915399  0.094170865  0.381492305
## 4         high income -6.650793651 -0.374054277 -0.029963498 -0.146205406
##      x.3rd Qu.       x.Max.
## 1 -0.580240080 -0.073856280
## 2 -0.006387768  0.249506033
## 3  1.129395767  1.858974359
## 4  0.422995824  2.023569024
## [1] ""
## [1] "N:"
##        Japanese Latin  American         Western           Other 
##              13              14              34               7 
## [1] ""
## [1] "Summary Statistics: "
##           Group.1      x.Min.   x.1st Qu.    x.Median      x.Mean
## 1        Japanese -0.39275956 -0.18603166  0.10555556  0.18350770
## 2 Latin  American -2.09939148 -0.29076011  0.02980310 -0.09352430
## 3         Western -6.65079365 -0.53312292 -0.05854851 -0.28229089
## 4           Other -0.07385628 -0.01260346  0.08595709  0.64666762
##     x.3rd Qu.      x.Max.
## 1  0.60500000  1.03563510
## 2  0.14691222  1.27500000
## 3  0.26615003  2.02356902
## 4  1.34040256  1.85897436
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  two years"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
##  63  63  49 
## [1] ""
## [1] "Summary Statistics for variable  comment_size"
##   Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean    x.3rd Qu.
## 1      CG -13.66666667  -0.50482582   0.25000000   0.07123241   1.16166667
## 2     CFM  -2.09361472  -0.16113855   0.04421657   0.07405147   0.46661041
## 3     CRM  -5.52691218  -0.55505708   0.11784512  -0.15606111   0.34800433
##         x.Max.
## 1  11.99829060
## 2   1.92638037
## 3   5.14795918
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "========================================================================"
## [1] "RESULTS FOR VARIABLE discussion_size"
## [1] "========================================================================"
## [1] ""
## [1] ""

## [1] ""

## [1] ""
## [1] "Boxplot on contributors only: "

## [1] ""
## [1] ""
## [1] "Time frame:  one month"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
## 218 123 189 
## [1] ""
## [1] "Summary Statistics for variable  discussion_size"
##   Group.1      x.Min.   x.1st Qu.    x.Median      x.Mean   x.3rd Qu.
## 1      CG -38.0000000   0.0000000   0.0000000  -0.2270642   0.0000000
## 2     CFM -94.0000000   0.0000000   0.0000000  -0.4641557   0.0000000
## 3     CRM -31.0000000   0.0000000   0.0000000   0.9649408   0.0000000
##        x.Max.
## 1   0.0000000
## 2  64.0000000
## 3  64.6666667
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  six months"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
## 185 102 139 
## [1] ""
## [1] "Summary Statistics for variable  discussion_size"
##   Group.1      x.Min.   x.1st Qu.    x.Median      x.Mean   x.3rd Qu.
## 1      CG -17.3076923   0.0000000   0.0000000   0.4334719   0.0000000
## 2     CFM -39.0000000   0.0000000   0.0000000   1.6546367   0.0000000
## 3     CRM -64.6666667   0.0000000   0.0000000  -1.1995889   0.0000000
##        x.Max.
## 1  34.5000000
## 2  61.0000000
## 3  55.0000000
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  one year"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
## 168  93 115 
## [1] ""
## [1] "Summary Statistics for variable  discussion_size"
##   Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean    x.3rd Qu.
## 1      CG  -75.0000000    0.0000000    0.0000000   -0.5375000    0.0000000
## 2     CFM -122.0000000    0.0000000    0.0000000   -0.1991574    0.0000000
## 3     CRM  -42.0000000    0.0000000    0.0000000   -0.4475362    0.0000000
##         x.Max.
## 1   35.2000000
## 2   51.0000000
## 3   34.5000000
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  two years"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
## 133  76  85 
## [1] ""
## [1] "Summary Statistics for variable  discussion_size"
##   Group.1     x.Min.  x.1st Qu.   x.Median     x.Mean  x.3rd Qu.
## 1      CG -19.000000   0.000000   0.000000   1.995166   0.000000
## 2     CFM -62.000000   0.000000   0.000000   2.557235   7.125000
## 3     CRM -23.777778   0.000000   0.000000   5.757111   0.000000
##       x.Max.
## 1  62.714286
## 2  65.000000
## 3  83.000000
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "========================================================================"
## [1] "RESULTS FOR VARIABLE notes_size"
## [1] "========================================================================"
## [1] ""
## [1] ""

## [1] ""

## [1] ""
## [1] "Boxplot on contributors only: "

## [1] ""
## [1] ""
## [1] "Time frame:  one month"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
## 218 123 189 
## [1] ""
## [1] "Summary Statistics for variable  notes_size"
##   Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean    x.3rd Qu.
## 1      CG -16.00000000   0.00000000   0.00000000  -0.06116208   0.00000000
## 2     CFM -46.00000000   0.00000000   0.00000000  -0.31066911   0.00000000
## 3     CRM -30.00000000   0.00000000   0.00000000  -0.23890988   0.00000000
##         x.Max.
## 1   9.66666667
## 2  11.00000000
## 3   6.33333333
## [1] ""
## [1] ""
## [1] "notes_size is significantly influenced by an event for one month"
## [1] ""
## [1] ""
## [1] "Pairwise comparison: "
##             CG        CFM
## CFM 0.09721944         NA
## CRM 0.92901542 0.09721944
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  six months"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
## 185 102 139 
## [1] ""
## [1] "Summary Statistics for variable  notes_size"
##   Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean    x.3rd Qu.
## 1      CG -11.50000000   0.00000000   0.00000000   0.21940798   0.00000000
## 2     CFM -13.33333333   0.00000000   0.00000000   0.75148760   0.78541667
## 3     CRM -38.00000000   0.00000000   0.00000000   0.01993748   0.00000000
##         x.Max.
## 1  17.40000000
## 2  14.00000000
## 3  26.50000000
## [1] ""
## [1] ""
## [1] "notes_size is significantly influenced by an event for six months"
## [1] ""
## [1] ""
## [1] "Pairwise comparison: "
##             CG        CFM
## CFM 0.02809269         NA
## CRM 0.76061625 0.06340557
## [1] "Cohends d for effect size of the CFM on notes_size :"
## 
## Cohen's d
## 
## d estimate: -0.1850486 (negligible)
## 95 percent confidence interval:
##       lower       upper 
## -0.42826972  0.05817259 
## [1] ""
## [1] "N:"
## [1] 102
## [1] "N:"
##          low income lower middle income upper middle income 
##                   4                   9                  26 
##         high income 
##                  63 
## [1] ""
## [1] "Summary Statistics: "
##               Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean
## 1          low income -13.33333333  -2.61458333   1.37916667  -2.17500000
## 2 lower middle income  -3.33333333   0.00000000   0.00000000   0.06831392
## 3 upper middle income  -3.65753425   0.00000000   0.00000000   1.41161521
## 4         high income  -4.00000000   0.00000000   0.00000000   0.76245896
##      x.3rd Qu.       x.Max.
## 1   1.81875000   1.87500000
## 2   0.30946399   2.39393939
## 3   0.66666667  14.00000000
## 4   0.42083333  12.00000000
## [1] ""
## [1] "N:"
##        Japanese Latin  American         Western           Other 
##              16              27              46              13 
## [1] ""
## [1] "Summary Statistics: "
##           Group.1       x.Min.    x.1st Qu.     x.Median       x.Mean
## 1        Japanese  -1.42708333  -0.16666667   0.00000000  -0.06167948
## 2 Latin  American -13.33333333   0.00000000   0.00000000   0.89381575
## 3         Western  -4.00000000   0.00000000   0.00000000   0.93200540
## 4           Other   0.00000000   0.00000000   0.00000000   0.81794872
##      x.3rd Qu.       x.Max.
## 1   0.00000000   1.71428571
## 2   0.56682207  14.00000000
## 3   0.83750000  12.00000000
## 4   1.52941176   4.47058824
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  one year"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
## 168  93 115 
## [1] ""
## [1] "Summary Statistics for variable  notes_size"
##   Group.1      x.Min.   x.1st Qu.    x.Median      x.Mean   x.3rd Qu.
## 1      CG -29.5000000   0.0000000   0.0000000   0.1524223   0.0000000
## 2     CFM -61.0000000   0.0000000   0.0000000   0.6470461   0.6363636
## 3     CRM -13.6000000   0.0000000   0.0000000  -0.1897661   0.0000000
##        x.Max.
## 1  35.5000000
## 2  51.0000000
## 3  14.6666667
## [1] ""
## [1] ""
## [1] ""
## [1] "--------------------------------------------------------------------------------"
## [1] ""
## [1] ""
## [1] ""
## [1] "Time frame:  two years"
## [1] ""
## [1] "N:"
##  CG CFM CRM 
## 133  76  85 
## [1] ""
## [1] "Summary Statistics for variable  notes_size"
##   Group.1     x.Min.  x.1st Qu.   x.Median     x.Mean  x.3rd Qu.
## 1      CG -27.833333   0.000000   0.000000   0.495525   0.000000
## 2     CFM -28.647059   0.000000   0.000000   1.751752   3.352733
## 3     CRM  -7.250000   0.000000   0.000000   1.635393   0.000000
##       x.Max.
## 1  49.000000
## 2  44.111111
## 3  54.000000
## [1] ""
## [1] ""
## [1] "notes_size is significantly influenced by an event for two years"
## [1] ""
## [1] ""
## [1] "Pairwise comparison: "
##             CG       CFM
## CFM 0.03929447        NA
## CRM 0.13319081 0.3097795
## [1] "Cohends d for effect size of the CFM on notes_size :"
## 
## Cohen's d
## 
## d estimate: -0.1591461 (negligible)
## 95 percent confidence interval:
##      lower      upper 
## -0.4430495  0.1247573 
## [1] ""
## [1] "N:"
## [1] 76
## [1] "N:"
##          low income lower middle income upper middle income 
##                   2                   7                  16 
##         high income 
##                  51 
## [1] ""
## [1] "Summary Statistics: "
##               Group.1      x.Min.   x.1st Qu.    x.Median      x.Mean
## 1          low income   2.6863799   3.3897849   4.0931900   4.0931900
## 2 lower middle income -17.3333333  -0.3152810   0.0000000  -1.2166109
## 3 upper middle income -11.0000000  -0.0312500   0.0000000   0.9002379
## 4         high income -28.6470588   0.0000000   0.0000000   2.3344951
##     x.3rd Qu.      x.Max.
## 1   4.7965950   5.5000000
## 2   2.0333333   5.3809524
## 3   2.4775000  13.8333333
## 4   3.0758145  44.1111111
## [1] ""
## [1] "N:"
##        Japanese Latin  American         Western           Other 
##              12              21              36               7 
## [1] ""
## [1] "Summary Statistics: "
##           Group.1        x.Min.     x.1st Qu.      x.Median        x.Mean
## 1        Japanese  -1.277777778   0.000000000   1.083333333   2.361784297
## 2 Latin  American -11.000000000   0.000000000   0.000000000   1.702554155
## 3         Western -28.647058824  -0.668999746   0.000000000   1.916237533
## 4           Other -17.333333333   0.000000000   0.000000000   0.007651628
##       x.3rd Qu.        x.Max.
## 1   2.225694444  13.000000000
## 2   4.000000000  26.000000000
## 3   3.555128205  44.111111111
## 4   1.776780698  13.833333333
## [1] ""
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## [1] ""
#rmarkdown::render("052-Seniors-Analyses.R", "html_document")